CN112462420A - Slope locking section intelligent positioning and feature identification method - Google Patents
Slope locking section intelligent positioning and feature identification method Download PDFInfo
- Publication number
- CN112462420A CN112462420A CN202011289495.6A CN202011289495A CN112462420A CN 112462420 A CN112462420 A CN 112462420A CN 202011289495 A CN202011289495 A CN 202011289495A CN 112462420 A CN112462420 A CN 112462420A
- Authority
- CN
- China
- Prior art keywords
- locking section
- monitoring
- microseismic
- slope
- data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
- 238000000034 method Methods 0.000 title claims abstract description 22
- 238000012544 monitoring process Methods 0.000 claims abstract description 62
- 239000011435 rock Substances 0.000 claims abstract description 9
- 238000013473 artificial intelligence Methods 0.000 claims abstract description 5
- 238000009434 installation Methods 0.000 claims abstract description 3
- 238000012545 processing Methods 0.000 claims abstract description 3
- 239000000523 sample Substances 0.000 claims description 20
- 238000010276 construction Methods 0.000 claims description 9
- 230000008569 process Effects 0.000 claims description 8
- 230000005540 biological transmission Effects 0.000 claims description 7
- 230000006378 damage Effects 0.000 claims description 7
- 238000005553 drilling Methods 0.000 claims description 3
- 238000009933 burial Methods 0.000 claims description 2
- 230000008859 change Effects 0.000 claims description 2
- 238000011900 installation process Methods 0.000 claims description 2
- 230000001681 protective effect Effects 0.000 claims description 2
- 230000002787 reinforcement Effects 0.000 abstract 2
- 238000005192 partition Methods 0.000 abstract 1
- 230000002265 prevention Effects 0.000 abstract 1
- 238000013461 design Methods 0.000 description 5
- 230000007246 mechanism Effects 0.000 description 3
- 238000009825 accumulation Methods 0.000 description 2
- 230000007547 defect Effects 0.000 description 2
- 230000001066 destructive effect Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 230000001133 acceleration Effects 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 230000001939 inductive effect Effects 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 230000004807 localization Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000005381 potential energy Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
- G01V1/288—Event detection in seismic signals, e.g. microseismics
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/34—Parallel operation in networks using both storage and other dc sources, e.g. providing buffering
- H02J7/35—Parallel operation in networks using both storage and other dc sources, e.g. providing buffering with light sensitive cells
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/65—Source localisation, e.g. faults, hypocenters or reservoirs
Landscapes
- Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Physics & Mathematics (AREA)
- Environmental & Geological Engineering (AREA)
- Remote Sensing (AREA)
- Geology (AREA)
- Business, Economics & Management (AREA)
- Acoustics & Sound (AREA)
- Emergency Management (AREA)
- General Life Sciences & Earth Sciences (AREA)
- General Physics & Mathematics (AREA)
- Geophysics (AREA)
- Power Engineering (AREA)
- Geophysics And Detection Of Objects (AREA)
- Devices Affording Protection Of Roads Or Walls For Sound Insulation (AREA)
Abstract
The invention belongs to the field of geotechnical engineering, and discloses a slope locking section intelligent positioning and feature recognition method which comprises the steps of (1) large-scale micro-seismic monitoring system installation and automatic monitoring, and (2) micro-seismic monitoring data automatic processing and locking section position preliminary recognition. And (3) accurately positioning the locking section and identifying the characteristics. The method determines the exact position of the rock slope locking section through the microseismic energy and the microseismic event on the basis of microseismic monitoring, determines the initial position of the locking section through an artificial intelligence algorithm and partitions of a slope monitoring area, and determines the characteristic dimension information of the locking section in more detail by adjusting the microseismic monitoring range after determining the initial position of the locking section, thereby providing a basis for the stability analysis of the locking type slope, providing reference for the slope reinforcement and landslide prevention and control, and reducing the slope reinforcement and monitoring range and cost.
Description
Technical Field
The invention relates to the field of slope monitoring, in particular to a slope locking section intelligent positioning and feature identification method
Background
Landslides, as a typical disastrous geological disaster, cause enormous economic loss and casualties on a global scale, thus leading to extensive research. However, due to the complexity of the landslide mechanism, the evolution of landslide is not yet fully understood. Due to the huge potential energy of the large-scale rocky landslide, a chain-type geological disaster with high speed, long distance and integration of 'collapse → slide → flow' is formed after the large-scale rocky landslide is separated from mother rocks, and destructive damage and serious casualties are often caused. The rock landslide relates to different geological environment conditions and geological structures, has different inducing mechanisms and triggering factors, and has extremely complex deformation, destruction and evolution mechanisms and generation processes. The locking section plays a key role in the sliding process of the rock slope, the locking section refers to a part which is not communicated on a sliding surface, bears stress concentration and provides a key bearing effect in the slope instability process, and the strength and deformation of the part determine the integral stability of the slope. Slopes can be classified into two broad categories, locked slopes and unlocked slopes, based on the presence or absence of a locking segment that controls the stability of the slope. It is emphasized that the locking segment has an energy-gathering effect, which stores a large amount of elastic strain energy before the locking segment is not penetrated through, and converts the elastic strain energy into slope kinetic energy when the locking segment is suddenly broken, resulting in high-speed starting of the landslide, so that the locking type slope is often strongly destructive after instability, and typical examples are extra-large landslide of showa shinkangtai village, mountains of shanghai, mountains of Chongqing Wulong mountains of cocktail landslide and the like. The slope of the locking section exists in the weak layer, if the through destruction does not occur in the locking section on the latent sliding surface, even if the slope creeps to slide under the action of factors such as rainfall and the like and the acceleration behavior occurs, the integral instability sliding cannot occur, and the locking section has obvious characteristics, so that the locking type slope is probably one of the global problems of slope instability prediction, namely that the strength is relatively weak and the most possibility is broken through firstly. In the research on the locking type side slope, the current means is mainly to carry out inversion analysis on the landslide process of the side slope according to geological data after landslide, and a method for finding the position and the characteristics of a locking section before landslide is lacked. Due to the lack of exact information of the locking section before design and construction, the stability design and construction of the side slope are influenced obviously. Therefore, the slope locking section intelligent positioning and feature identification method provided by the invention is very necessary.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provides a slope locking section intelligent positioning and feature recognition method. The method can solve the engineering problem that the position and the characteristic information of the positioning and locking section cannot be accurately judged at present, makes up the defects of conventional design of the side slope, and can more reasonably and accurately analyze the stability of the side slope and beneficially guide the design, monitoring and construction processes of the side slope.
In order to solve the technical problems, the invention is realized by the following technical scheme:
a slope locking section intelligent positioning and feature recognition method comprises the following steps:
step (1) installation and automatic monitoring of large-scale micro-seismic monitoring system
And (3) defining a side slope monitoring range according to the side slope geological data and the engineering construction requirement, and dividing the side slope in the range to be monitored into different grids according to the elevation and the transverse and longitudinal spacing. And a guided wave rod is installed in the middle of the divided grids through drilling, and a micro-seismic automatic monitoring probe is installed at a port above the guided wave rod. The automatic micro-seismic monitoring probe comprises a sensor, wireless transmission equipment, a solar cell panel, a storage battery, a protective box body and the like. Microseismic event data generated when external factors such as rainfall, earthquake, construction and the like change are collected by the automatic monitoring probe and remotely transmitted to the data processing center.
Step (2) automatic processing of microseismic monitoring data and primary identification of position of locking segment
Because the locking section has higher strength, a large amount of elastic strain energy is gathered at the locking section, the locking section can be more strongly damaged in the process of external disturbance of the slope, and the energy can be released outwards in the form of waves. Waves caused by the same microseismic event are received by a plurality of monitoring probes at different positions and buried depths and then are remotely transmitted to a data center. The data center effectively eliminates external interference data from the received real-time micro-seismic monitoring data by adopting an artificial intelligence method, and keeps the micro-seismic monitoring result generated by deformation and damage of the rock mass. The location of the microseismic event and the energy concentration zone can be determined via a double-differenced localization algorithm to make a preliminary determination of the locking segment location.
Step (3) accurate positioning and feature recognition of locking section
And (3) on the basis of the primary positioning position of the locking section in the step (2), reducing the microseismic monitoring range, subdividing the obtained energy gathering area into different grids, repeating the installation process of the microseismic monitoring system in the step (1), and installing automatic monitoring probes at different burial depth positions in the range of the energy gathering area defined in the step (2). Microseismic monitoring is again performed on this region. And then the obtained monitoring data is processed again to obtain more detailed information such as the position, the size and the like of the locking section. Through comparing the microseismic data information of different rock masses in the database, other dimension information of the locking section can be obtained. Compared with the prior art, the invention has the following advantages:
through the micro-seismic data monitoring probe of intelligence, can be long-rangely monitor the side slope. Adopt solar cell panel to provide the energy for probe and transmission equipment, high-efficient environmental protection has avoided the destruction of transmission optical cable because of construction and external reason cause simultaneously, reduces labour cost and transmission optical cable expense, saves the investment. The artificial intelligence technology is adopted to process the monitoring data, and the slope monitoring data can be efficiently picked up. Adopt many rounds of location, can carry out accurate location to the locking section. Through the accurate positioning analysis to the locking section, can provide favorable direction for design construction monitoring, ensure the stability and the safety of side slope.
Drawings
FIG. 1 is a cross-sectional view of a locking section microseismic automatic monitoring probe;
FIG. 2 is a cross-sectional view of the locking section microseismic monitoring system arrangement;
FIG. 3 is a top view of the locking segment preliminary identification microseismic monitoring system arrangement;
FIG. 4 is a top view of a locking segment accurate identification microseismic monitoring system arrangement;
in the figure: 1-locking section micro-seismic automatic monitoring probe, 2-solar panel, 3-solar panel angle adjusting support, 4-protecting box, 5-wave guide rod, 6-micro-seismic monitoring probe, 7-solar storage battery and 8-wireless data transmission equipment.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without inventive effort based on the embodiments of the present invention, are within the scope of the present invention.
Examples
As shown in figure 1, the locking section micro-seismic automatic monitoring probe comprises a 2-solar panel, a 3-solar panel angle adjusting support, a 4-protective box body, a 6-micro-seismic monitoring probe, a 7-solar storage battery and 8-wireless data transmission equipment. The mounting position of the locking section micro-seismic automatic monitoring probe is firstly determined according to the geological data of the side slope and the engineering construction requirements, the side slope in the monitoring range to be monitored is divided into different grids according to the elevation and the horizontal and longitudinal spacing, the middle part of the divided grids is provided with a guide wave rod through drilling, and the port above the guide wave rod is provided with the automatic micro-seismic monitoring probe.
As shown in FIG. 2, the energy accumulated by the locking segment is released in the form of elastic waves under external disturbance, and the destruction waveforms caused by the same microseismic event are received by the automatic monitoring probes at different positions and then are remotely transmitted to the data processing center. And the data processing center adopts an artificial intelligence method to pick up the obtained microseismic monitoring data. And determining the position and energy of the microseismic event by a double-difference positioning algorithm. As shown in fig. 3, the microseismic monitoring range is wide, so the first round of monitoring can only determine the position of the locking section preliminarily.
As shown in fig. 4, on the basis of the primary positioning of the locking section, the microseismic monitoring range is continuously reduced, the obtained energy accumulation area is subdivided into different grids again, and the microseismic monitoring is intensively performed on the energy accumulation area obtained by the primary positioning. And then the obtained monitoring data is processed again to obtain the more exact position of the locking section. The monitoring range may be subdivided further if necessary. And then comparing the obtained information of the microseismic event energy and the like with the existing rock mass microseismic information in the database, and further obtaining other dimension information of the locking section.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (1)
1. A slope locking section intelligent positioning and feature identification method is characterized by comprising the following steps:
step (1) installation and automatic monitoring of large-scale micro-seismic monitoring system
Defining a side slope monitoring range according to side slope geological data and engineering construction requirements, and dividing the side slope in the range to be monitored into different grids according to elevation and transverse and longitudinal intervals; installing a guided wave rod in the middle of the divided grids through drilling, and installing a microseismic monitoring probe at a port above the guided wave rod; the microseism monitoring probe mainly comprises a sensor, wireless data transmission equipment, a solar panel, a solar storage battery and a protective box body; microseismic event data generated when external factors change are collected by a microseismic monitoring probe and remotely transmitted to a data processing center;
step (2) automatic processing of microseismic monitoring data and primary identification of position of locking segment
Because the locking section has higher strength, a large amount of elastic strain energy is gathered at the locking section, the locking section can be more strongly damaged in the process of external disturbance of the slope, and the energy can be released outwards in the form of waves; the waves caused by the same microseismic event are received by a plurality of microseismic monitoring probes at different positions and buried depths and then are remotely transmitted to a data processing center; the data processing center eliminates external interference data from the received real-time microseismic monitoring data by adopting an artificial intelligence method, and keeps microseismic monitoring results generated by deformation and damage of rock masses; determining the location of the microseismic event and the energy gathering zone via a double-difference location algorithm to initially determine the location of the locking segment;
step (3) accurate positioning and feature recognition of locking section
On the basis of the primary positioning position of the locking section in the step (2), reducing the microseismic monitoring range, subdividing the obtained energy gathering area into different grids, repeating the installation process of the microseismic monitoring system in the step (1), and installing microseismic monitoring probes at different burial depth positions in the range of the energy gathering area defined in the step (2); the area is subjected to microseismic monitoring again; then, the obtained monitoring data is processed again to obtain more detailed position and size information of the locking section; and obtaining other dimension information of the locking section by comparing the microseismic data information of different rock masses in the database.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011289495.6A CN112462420A (en) | 2020-11-17 | 2020-11-17 | Slope locking section intelligent positioning and feature identification method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011289495.6A CN112462420A (en) | 2020-11-17 | 2020-11-17 | Slope locking section intelligent positioning and feature identification method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112462420A true CN112462420A (en) | 2021-03-09 |
Family
ID=74837585
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011289495.6A Withdrawn CN112462420A (en) | 2020-11-17 | 2020-11-17 | Slope locking section intelligent positioning and feature identification method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112462420A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114137605A (en) * | 2021-10-21 | 2022-03-04 | 陕西延长石油矿业有限责任公司 | Intelligent positioning and feature identification method for rock bridge in coal mine rock mass |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105116440A (en) * | 2015-09-11 | 2015-12-02 | 中铁十九局集团矿业投资有限公司 | Side slope rock monitoring system and method |
| CN105549077A (en) * | 2015-12-16 | 2016-05-04 | 中国矿业大学(北京) | Micro-earthquake epicenter positioning method calculated based on multilevel multi-scale grid similarity coefficient |
| CN105954795A (en) * | 2016-04-25 | 2016-09-21 | 吉林大学 | Grid successive dissection method used for microseismic positioning |
| CN209619984U (en) * | 2018-07-28 | 2019-11-12 | 中铁二院工程集团有限责任公司 | Railway high precipitous rock slope Microseismic monitoring system |
-
2020
- 2020-11-17 CN CN202011289495.6A patent/CN112462420A/en not_active Withdrawn
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105116440A (en) * | 2015-09-11 | 2015-12-02 | 中铁十九局集团矿业投资有限公司 | Side slope rock monitoring system and method |
| CN105549077A (en) * | 2015-12-16 | 2016-05-04 | 中国矿业大学(北京) | Micro-earthquake epicenter positioning method calculated based on multilevel multi-scale grid similarity coefficient |
| CN105954795A (en) * | 2016-04-25 | 2016-09-21 | 吉林大学 | Grid successive dissection method used for microseismic positioning |
| CN209619984U (en) * | 2018-07-28 | 2019-11-12 | 中铁二院工程集团有限责任公司 | Railway high precipitous rock slope Microseismic monitoring system |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114137605A (en) * | 2021-10-21 | 2022-03-04 | 陕西延长石油矿业有限责任公司 | Intelligent positioning and feature identification method for rock bridge in coal mine rock mass |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Xue et al. | Rockburst prediction and stability analysis of the access tunnel in the main powerhouse of a hydropower station based on microseismic monitoring | |
| CN108412547B (en) | Pressure-bearing fault activation water inrush multi-field information collaborative monitoring impending forecasting method and monitoring system | |
| CN108922123B (en) | mine slope slip stability monitoring and early warning method | |
| CN103291364A (en) | Microseismic multidimensional information comprehensive time sequence early warning method for rock burst | |
| CN108510112A (en) | A kind of mine disaster prediction and warning method that field monitoring is combined with numerical simulation | |
| CN111042866B (en) | Multi-physical-field cooperative water inrush monitoring method | |
| CN107727737A (en) | One kind excavates the unknown geological structure activation recognition methods of underground engineering under Unloading Effect | |
| CN116591777B (en) | Multi-field multi-source information fusion rock burst intelligent monitoring and early warning device and method | |
| CN114412573B (en) | Mine wall breakage monitoring and early warning system and method | |
| CN112462420A (en) | Slope locking section intelligent positioning and feature identification method | |
| CN114109508A (en) | Rock burst monitoring method based on energy system analysis and application | |
| CN115095389A (en) | Rock burst monitoring and early warning system based on coal rock charge signals | |
| CN117189239B (en) | Tunnel surrounding rock damage monitoring method | |
| CN113591347A (en) | Dynamic monitoring method and early warning system in high slope construction process | |
| CN116677458A (en) | Shallow bias tunnel blasting vibration multifunctional monitoring and early warning system | |
| CN114596692B (en) | Underground railway and pipe gallery protection area structure monitoring and early warning emergency system | |
| CN114399088A (en) | Method for predicting stability of mine goaf | |
| CN114354762A (en) | Coal rock instability destruction precursor information identification method | |
| CN110532703B (en) | Seabed safety management method and system for sea area segment submarine tunnel | |
| CN113434819A (en) | Method for determining influence time and distance of working face mining on mine earthquake activity of goaf | |
| CN108319915B (en) | Multi-time-window simplified form identification method for dynamically adjusting rock burst signal threshold | |
| CN113586157B (en) | Extraction working face salient dangerous area rapid division method based on Kriging interpolation | |
| CN117741734B (en) | Stress measurement method of tunnel surrounding rock and application of stress measurement method in rock burst prevention and control | |
| Lian et al. | Design and implementation of mine water hazard monitoring and early warning platform | |
| CN117607973B (en) | Method for distinguishing space-time dynamic activation degree of collapse column |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WW01 | Invention patent application withdrawn after publication | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20210309 |